Gene Expression Profiling at Birth Characterizing the Preterm Infant with Early Onset Infection

Total Page:16

File Type:pdf, Size:1020Kb

Gene Expression Profiling at Birth Characterizing the Preterm Infant with Early Onset Infection JMolMed DOI 10.1007/s00109-016-1466-4 ORIGINAL ARTICLE Gene expression profiling at birth characterizing the preterm infant with early onset infection Anne Hilgendorff1,2 & Anita Windhorst 3,4 & Manuel Klein5 & Svetlin Tchatalbachev3 & Christine Windemuth-Kieselbach6 & Joachim Kreuder2 & Matthias Heckmann7 & Anna Gkatzoflia2 & Harald Ehrhardt2 & Josef Mysliwietz8 & Michael Maier3 & Benjamin Izar3,9 & Andre Billion3 & Ludwig Gortner10 & Trinad Chakraborty3 & Hamid Hossain3 Received: 26 August 2015 /Revised: 9 August 2016 /Accepted: 18 August 2016 # The Author(s) 2016. This article is published with open access at Springerlink.com Abstract with EOI could be further differentiated into two subclasses Early onset infection (EOI) in preterm infants <32 weeks ges- and were distinguished by the magnitude of the expression of tational age (GA) is associated with a high mortality rate and genes involved in both neutrophil and T cell activation. A the development of severe acute and long-term complications. hallmark activity for both subclasses of EOI was a common The pathophysiology of EOI is not fully understood and clin- suppression of genes involved in natural killer (NK) cell func- ical and laboratory signs of early onset infections in this pa- tion, which was independent from NK cell numbers. tient cohort are often not conclusive. Thus, the aim of this Significant results were recapitulated in an independent vali- study was to identify signatures characterizing preterm infants dation cohort. Gene expression profiling may enable early and with EOI by using genome-wide gene expression (GWGE) more precise diagnosis of EOI in preterm infants. analyses from umbilical arterial blood of preterm infants. This prospective cohort study was conducted in preterm in- Key message fants <32 weeks GA. GWGE analyses using CodeLink hu- & Gene expression (GE) profiling at birth characterizes pre- man microarrays were performed from umbilical arterial term infants with EOI. blood of preterm infants with and without EOI. GWGE anal- & GE analysis indicates dysregulation of NK cell activity. yses revealed differential expression of 292 genes in preterm & NK cell activity at birth may be a useful marker to improve infants with EOI as compared to infants without EOI. Infants early diagnosis of EOI. Anne Hilgendorff and Anita Windhorst contributed equally to the study. Electronic supplementary material The online version of this article (doi:10.1007/s00109-016-1466-4) contains supplementary material, which is available to authorized users. * Hamid Hossain 4 Institute for Medical Informatics, Justus-Liebig-University Giessen, [email protected] Giessen, Germany 5 Hospital Barmherzige Brueder, Regensburg, Germany 1 Department of Neonatology, Grosshadern, Ludwig-Maximilian 6 Institute of Medical Biometry and Epidemiology, University Munich, Germany and the Comprehensive Pneumology Philipps-University Marburg, Marburg, Germany Center, Helmholtz Zentrum Muenchen, Munich, Germany, Member of the German Center for Lung Research (DZL), Munich, Germany 7 Department of Neonatology and Pediatric Intensive Care, University Medicine, Greifswald, Germany 2 Department of Pediatrics and Neonatology, Justus-Liebig University 8 Giessen, Germany, Member of the German Center for Lung Research Institute for Molecular Immunology, Helmholtz Center Munich, (DZL), Giessen, Germany Munich, Germany 9 Broad Institute of MIT and Harvard, Cambridge, MA, USA 3 Institute for Medical Microbiology, Justus-Liebig University Giessen, Member of the German Center for Infection Research 10 Department of Pediatrics and Neonatology, University of Saarland, (DZIF), Schubertstr. 81, 35392 Giessen, Germany Homburg, Germany J Mol Med Keywords Neonatal sepsis . Gene expression profiling Patients were allocated to one of the two following groups: (I) EOI and (II) non-EOI (no signs of infection in the first 72 h of life). EOI was diagnosed if the infant showed both a pathologic Introduction ratio of immature to total granulocytes (IT ratio ≥ 0.2 as deter- mined by manual counts) and/or a pathologic white blood cell Preterm birth (PTB) remains a major problem in perinatal medi- count paralleled or followed by an increase in CRP ≥ 6mg/lin cine and accounts for 75 % of the perinatal mortality and 50 % of the first 72 h of life [7, 10–14]. These laboratory signs had to be the perinatal morbidity [1]. Early onset infections (EOI) in PTB are accompanied by at least three of the following clinical signs associated with significant morbidity and a mortality rate of 15– suggestive of bacterial infection in the new born infants: pallor, 50 %, especially in very immature preterm infants [2, 3]. Although gray skin color, capillary refill >3 s, requiring volume resuscita- clinical and experimental studies continue to provide valuable in- tion or substitution of any catecholamines, dyspnea, tachypnea, sight into processes leading to EOI and its attendant complications requiring respiratory support or supplemental oxygen, increased [4, 5], biological pathways relevant to the complex pathophysiol- thermal instability, unexplained hypo- and hyperglycemia, feed- ogy of EOI remain poorly understood. This is reflected in the ing difficulties, bilious reflux and abdominal distension, increas- limitations of early diagnostic markers and the absence of targeted ing incidence of apnea and/or bradycardia, lethargy, irritability, treatment approaches in this high-risk patient cohort. Clinical signs and increased or decreased muscle tone [2, 15]. All patients who are ambiguous and difficult to interpret in the absence of reliable did not meet the criteria for the EOI were considered as non-EOI. early biochemical markers [6–8]. The gold standard of blood The characteristics and clinical parameters in the first 72 h of life culture-proven sepsis severely underestimates the rate of severe of the patient cohort are given in Table 1 (exploration cohort). P infections in newborns and especially preterm infants, as the diag- values were calculated using Fisher’s exact test for qualitative nostic approach is complicated by maternal antibiotic therapy and parameters and Wilcoxon U test for quantitative parameters. hampered by small blood volumes [2, 9]. As outcome and prog- The comprehensive monitoring of the perinatal course is fur- nosis of EOI mainly depend on early and efficient treatment, sen- ther defined in Supplemental Materials and Methods. The study sitive and specific indicators of EOI are crucial at the earliest stage has been approved by the legal ethical committee (File 79/01, of disease. University of Giessen, Germany). In this prospective cohort study, we applied gene expres- sion profiling from umbilical arterial blood of preterm infants Blood sampling, RNA isolation, and microarrays <32 weeks of gestational age to provide comprehensive bio- logical information and identify biological pathways relevant Blood for standard laboratory analyses including WBC and for the development of EOI in order to enable the identifica- blood samples for transcriptome analyses were obtained from tion of early diagnostic markers. an indwelling umbilical artery catheter immediately after birth. WBCs were repeated upon clinical indication in the later postna- tal course as a possible indicator of developing (congenital and Material and methods nosocomial) infections. Details of the microarray experiments and data analysis can be found in Supplemental Materials and Patients Methods. Briefly, 250–300 μl of umbilical arterial blood was obtained Newborn infants <32 weeks gestational age (GA) were prospec- immediately after birth from an indwelling umbilical artery cath- tively included in this study. eter and directly transferred to 750–900 μl of the PAXgene Depending on the availability of diagnostic criteria at birth, Blood RNA System (PreAnalytiX, Heidelberg, Germany). infants were pro- or retrospectively excluded when one of the RNA isolation was performed according to the manufacturer’s following diagnoses was present: premature rupture of mem- recommendations (PreAnalytiX). RNA was hybridized on branes ≥3 weeks prior to birth leading to oligo- or anhydramnios, CodeLink UniSet Human 10 K Bioarrays (GE Healthcare) using severe congenital malformations, diagnosis of severe metabolic the CodeLink Expression Assay Kit (GE Healthcare) and sam- disorders, prepartum treatment of the mother with cytostatic or ples processed using CodeLink Expression Software V4.1 (GE immunosuppressive medication other than for lung maturation, Healthcare). and postnatal treatment with corticosteroids in a dose ≥1 mg/kg body weight. Analysis of C-reactive protein (CRP), whole white Gene expression analysis blood count (WBC), and microbiological examination of blood cultures, swabs, urine, and stool samples were carried out in the In order to account for confounding effects of WBCs on the first 72 h of life. Patients were clinically re-evaluated in short transcriptome pattern, we evaluated differences between EOI intervals and continuously monitored for vital signs, i.e., heart and non-EOI preterm infants in their differential WBCs at rate, blood pressure, microcirculation, and breathing pattern. birth by using the Wilcoxon rank-sum test. Missing data from JMolMed Table 1 Neonatal characteristics of preterm infants EOI Non-EOI (control) P value n 16 8 GA (weeks) 29 (24–30) 31 (29–31) 0.008 Birth weight (g) 1085 (590–1730) 1445 (900–1760) 0.046 IUGR 1 (6.25 %) 1 (12.25 %) 1 ANCS 6 (37.5 %)/a9 (56.3 %) 6 (75 %)/a6 (75 %) 0.667/a1 Chorioamnionitis 8 (50 %) 0 0.081 PROM 1 (6.25 %) 0 1 C-section 15 (93.75 %) 8 (100 %) 1 CRIB 6 (1–17) 1 (0–13) 0.102 RDS 16 (100 %) 7 (87.5 %) 0.333 RDS ≥ grade III 9 (56.3 %) 1 (12.5 %) 0.079 IVH 7 (43.75 %) 1 (12.5 %) 0.189 BPD 10 (62.5 %) 0 0.002 Length of mechanical ventilation (days) 7 (3–44) 0 (0–7) <0.001 ROP 9 (69 %) 4 (50 %) 0.646 Length of hospital stay (days) 70 (10–138) 47 (23–89) 0.065 Death 1 (6.25 %) 0 1 Blood culture positive 1 (6.25 %) 0 1 b b ITmax 0.32 (0.11–0.8) 0.17 (0.04–0.37) 0.018 b b CRPmax (mg/dl) 17.8 (7.1–52.3) 4(4–5.5) <0.001 Data are given as median and range or percent of total in group.
Recommended publications
  • Single-Cell Profiling Identifies Impaired Adaptive NK Cells Expanded After HCMV Reactivation in Haploidentical HSCT
    Single-cell profiling identifies impaired adaptive NK cells expanded after HCMV reactivation in haploidentical HSCT Elisa Zaghi, … , Enrico Lugli, Domenico Mavilio JCI Insight. 2021;6(12):e146973. https://doi.org/10.1172/jci.insight.146973. Research Article Hematology Immunology Graphical abstract Find the latest version: https://jci.me/146973/pdf RESEARCH ARTICLE Single-cell profiling identifies impaired adaptive NK cells expanded after HCMV reactivation in haploidentical HSCT Elisa Zaghi,1 Michela Calvi,1,2 Simone Puccio,3 Gianmarco Spata,1 Sara Terzoli,1 Clelia Peano,4 Alessandra Roberto,3 Federica De Paoli,3 Jasper J.P. van Beek,3 Jacopo Mariotti,5 Chiara De Philippis,5 Barbara Sarina,5 Rossana Mineri,6 Stefania Bramanti,5 Armando Santoro,5 Vu Thuy Khanh Le-Trilling,7 Mirko Trilling,7 Emanuela Marcenaro,8 Luca Castagna,5 Clara Di Vito,1,2 Enrico Lugli,3,9 and Domenico Mavilio1,2 1Unit of Clinical and Experimental Immunology, IRCCS Humanitas Research Hospital, Rozzano, Milan, Italy. 2BIOMETRA, Università degli Studi di Milano, Milan, Italy. 3Laboratory of Translational Immunology, 4Institute of Genetic and Biomedical Research, UoS Milan, National Research Council, and Genomic Unit, 5Bone Marrow Transplant Unit, and 6Molecular Biology Section, Clinical Investigation Laboratory, IRCCS Humanitas Research Hospital, Milan, Italy. 7Institute for Virology, University Hospital Essen, University Duisburg-Essen, Essen, Germany. 8Department of Experimental Medicine, University of Genoa, Genoa, Italy. 9Flow Cytometry Core, IRCCS Humanitas Research Hospital, Milan, Italy. Haploidentical hematopoietic stem cell transplantation (h-HSCT) represents an efficient curative approach for patients affected by hematologic malignancies in which the reduced intensity conditioning induces a state of immunologic tolerance between donor and recipient.
    [Show full text]
  • Supplementary Table 1: Adhesion Genes Data Set
    Supplementary Table 1: Adhesion genes data set PROBE Entrez Gene ID Celera Gene ID Gene_Symbol Gene_Name 160832 1 hCG201364.3 A1BG alpha-1-B glycoprotein 223658 1 hCG201364.3 A1BG alpha-1-B glycoprotein 212988 102 hCG40040.3 ADAM10 ADAM metallopeptidase domain 10 133411 4185 hCG28232.2 ADAM11 ADAM metallopeptidase domain 11 110695 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 195222 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 165344 8751 hCG20021.3 ADAM15 ADAM metallopeptidase domain 15 (metargidin) 189065 6868 null ADAM17 ADAM metallopeptidase domain 17 (tumor necrosis factor, alpha, converting enzyme) 108119 8728 hCG15398.4 ADAM19 ADAM metallopeptidase domain 19 (meltrin beta) 117763 8748 hCG20675.3 ADAM20 ADAM metallopeptidase domain 20 126448 8747 hCG1785634.2 ADAM21 ADAM metallopeptidase domain 21 208981 8747 hCG1785634.2|hCG2042897 ADAM21 ADAM metallopeptidase domain 21 180903 53616 hCG17212.4 ADAM22 ADAM metallopeptidase domain 22 177272 8745 hCG1811623.1 ADAM23 ADAM metallopeptidase domain 23 102384 10863 hCG1818505.1 ADAM28 ADAM metallopeptidase domain 28 119968 11086 hCG1786734.2 ADAM29 ADAM metallopeptidase domain 29 205542 11085 hCG1997196.1 ADAM30 ADAM metallopeptidase domain 30 148417 80332 hCG39255.4 ADAM33 ADAM metallopeptidase domain 33 140492 8756 hCG1789002.2 ADAM7 ADAM metallopeptidase domain 7 122603 101 hCG1816947.1 ADAM8 ADAM metallopeptidase domain 8 183965 8754 hCG1996391 ADAM9 ADAM metallopeptidase domain 9 (meltrin gamma) 129974 27299 hCG15447.3 ADAMDEC1 ADAM-like,
    [Show full text]
  • Supporting Info
    advances.sciencemag.org/cgi/content/full/6/29/eaba9589/DC1 Supplementary Materials for Cell invasion in digital microfluidic microgel systems Bingyu B. Li, Erica Y. Scott, M. Dean Chamberlain, Bill T. V. Duong, Shuailong Zhang, Susan J. Done, Aaron R. Wheeler* *Corresponding author. Email: [email protected] Published 15 July 2020, Sci. Adv. 6, eaba9589 (2020) DOI: 10.1126/sciadv.aba9589 This PDF file includes: Figs. S1 to S8 Tables S1 and S2 References Supplementary Figure S1 CIMMS microgels and cell viability. For (a-c) core-shell microgels were formed from 2.4 mg/mL collagen I and 10% BM extract. (a) Cartoon indicating the orientation of the microgel shown in the images. SEM images of (b) the collagen I core (scale bar = 20 µm) and (c) the edge of microgel with core on the "top" and the shell on the "bottom" (scale bar = 100 µm). The pore size of the collagen I core was calculated to be 3.1 m by the method reported by Blackmon et al. (53), which is nearly identical to the pore size reported for the same concentration of collagen I cast in well plates by Lang et al. (54). For (d-f) MDA-MB-231 cells were seeded onto simple collagen I microgels (2.4 mg/mL). (d) Cell count per droplet with seeding density at 200,000 (lt. pink), 400,000 (fuscia) or 600,000 cells/mL (burgundy). Error bars represent ± 1 std. dev. from n = 4 microgels per condition. (e) 3D confocal fluorescent microscopy image of cells stained on day 4 with calcein-AM (live-green) and propidium iodide (dead-red).
    [Show full text]
  • Supplementary Table S4. FGA Co-Expressed Gene List in LUAD
    Supplementary Table S4. FGA co-expressed gene list in LUAD tumors Symbol R Locus Description FGG 0.919 4q28 fibrinogen gamma chain FGL1 0.635 8p22 fibrinogen-like 1 SLC7A2 0.536 8p22 solute carrier family 7 (cationic amino acid transporter, y+ system), member 2 DUSP4 0.521 8p12-p11 dual specificity phosphatase 4 HAL 0.51 12q22-q24.1histidine ammonia-lyase PDE4D 0.499 5q12 phosphodiesterase 4D, cAMP-specific FURIN 0.497 15q26.1 furin (paired basic amino acid cleaving enzyme) CPS1 0.49 2q35 carbamoyl-phosphate synthase 1, mitochondrial TESC 0.478 12q24.22 tescalcin INHA 0.465 2q35 inhibin, alpha S100P 0.461 4p16 S100 calcium binding protein P VPS37A 0.447 8p22 vacuolar protein sorting 37 homolog A (S. cerevisiae) SLC16A14 0.447 2q36.3 solute carrier family 16, member 14 PPARGC1A 0.443 4p15.1 peroxisome proliferator-activated receptor gamma, coactivator 1 alpha SIK1 0.435 21q22.3 salt-inducible kinase 1 IRS2 0.434 13q34 insulin receptor substrate 2 RND1 0.433 12q12 Rho family GTPase 1 HGD 0.433 3q13.33 homogentisate 1,2-dioxygenase PTP4A1 0.432 6q12 protein tyrosine phosphatase type IVA, member 1 C8orf4 0.428 8p11.2 chromosome 8 open reading frame 4 DDC 0.427 7p12.2 dopa decarboxylase (aromatic L-amino acid decarboxylase) TACC2 0.427 10q26 transforming, acidic coiled-coil containing protein 2 MUC13 0.422 3q21.2 mucin 13, cell surface associated C5 0.412 9q33-q34 complement component 5 NR4A2 0.412 2q22-q23 nuclear receptor subfamily 4, group A, member 2 EYS 0.411 6q12 eyes shut homolog (Drosophila) GPX2 0.406 14q24.1 glutathione peroxidase
    [Show full text]
  • High-Dimensional Analysis Reveals a Distinct Population of Adaptive-Like Tissue
    bioRxiv preprint doi: https://doi.org/10.1101/2019.12.20.883785; this version posted December 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 1 High-dimensional analysis reveals a distinct population of adaptive-like tissue- 2 resident NK cells in human lung 3 4 Nicole Marquardt1*, Marlena Scharenberg1, Jeffrey E. Mold2, Joanna Hård2, Eliisa 5 Kekäläinen3,4, Marcus Buggert1, Son Nguyen5,6, Jennifer N. Wilson1, Mamdoh Al- 6 Ameri7, Hans-Gustaf Ljunggren1, Jakob Michaëlsson1 7 8 Running title: Adaptive-like human lung tissue-resident NK cells 9 10 Affiliations: 11 1Center for Infectious Medicine, Department of Medicine, Karolinska Institutet, 12 Stockholm, Sweden 13 2Department of Cell and Molecular Biology, Karolinska Institutet, Stockholm, Sweden 14 3Translational Immunology Research Program & Department of Bacteriology and 15 Immunology, University of Helsinki, Finland 16 4HUSLAB, Division of Clinical Microbiology, Helsinki University Hospital, Helsinki, 17 Finland, 18 5Department of Microbiology, Perelman School of Medicine, University of 19 Pennsylvania, Philadelphia, PA, USA 20 6Institute for Immunology, Perelman School of Medicine, University of Pennsylvania, 21 Philadelphia, PA, USA 22 7Thoracic Surgery, Department of Molecular Medicine and Surgery, Karolinska 23 Institutet, Karolinska University Hospital, Stockholm, Sweden 24 1 bioRxiv preprint doi: https://doi.org/10.1101/2019.12.20.883785; this version posted December 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.
    [Show full text]
  • Type of the Paper (Article
    Supplementary figures and tables E g r 1 F g f2 F g f7 1 0 * 5 1 0 * * e e e * g g g * n n n * a a a 8 4 * 8 h h h * c c c d d d * l l l o o o * f f f * n n n o o o 6 3 6 i i i s s s s s s e e e r r r p p p x x x e e e 4 2 4 e e e n n n e e e g g g e e e v v v i i i t t t 2 1 2 a a a l l l e e e R R R 0 0 0 c o n tro l u n in fla m e d in fla m e d c o n tro l u n in fla m e d in fla m e d c o n tro l u n in fla m e d in fla m e d J a k 2 N o tc h 2 H if1 * 3 4 6 * * * e e e g g g n n n a a * * a * h h * h c c c 3 * d d * d l l l * o o o f f 2 f 4 n n n o o o i i i s s s s s s e e e r r 2 r p p p x x x e e e e e e n n n e e 1 e 2 g g g e e 1 e v v v i i i t t t a a a l l l e e e R R R 0 0 0 c o n tro l u n in fla m e d in fla m e d c o n tro l u n in fla m e d in fla m e d c o n tro l u n in fla m e d in fla m e d Z e b 2 C d h 1 S n a i1 * * 7 1 .5 4 * * e e e g g g 6 n n n * a a a * h h h c c c 3 * d d d l l l 5 o o o f f f 1 .0 * n n n * o o o i i i 4 * s s s s s s e e e r r r 2 p p p x x x 3 e e e e e e n n n e e e 0 .5 g g g 2 e e e 1 v v v i i i t t t a a a * l l l e e e 1 * R R R 0 0 .0 0 c o n tro l u n in fla m e d in fla m e d c o n tro l u n in fla m e d in fla m e d c o n tro l u n in fla m e d in fla m e d M m p 9 L o x V im 2 0 0 2 0 8 * * * e e e * g g g 1 5 0 * n n n * a a a * h h h * c c c 1 5 * 6 d d d l l l 1 0 0 o o o f f f n n n o o o i i i 5 0 s s s s s s * e e e r r r 1 0 4 3 0 p p p * x x x e e e * e e e n n n e e e 2 0 g g g e e e 5 2 v v v i i i t t t a a a l l l 1 0 e e e R R R 0 0 0 c o n tro l u n in fla m e d in fla m e d c o n tro l u n in fla m e d in fla m e d c o n tro l u n in fla m e d in fla m e d Supplementary Figure 1.
    [Show full text]
  • Supplementary Table 1
    Supplementary Table 1. 492 genes are unique to 0 h post-heat timepoint. The name, p-value, fold change, location and family of each gene are indicated. Genes were filtered for an absolute value log2 ration 1.5 and a significance value of p ≤ 0.05. Symbol p-value Log Gene Name Location Family Ratio ABCA13 1.87E-02 3.292 ATP-binding cassette, sub-family unknown transporter A (ABC1), member 13 ABCB1 1.93E-02 −1.819 ATP-binding cassette, sub-family Plasma transporter B (MDR/TAP), member 1 Membrane ABCC3 2.83E-02 2.016 ATP-binding cassette, sub-family Plasma transporter C (CFTR/MRP), member 3 Membrane ABHD6 7.79E-03 −2.717 abhydrolase domain containing 6 Cytoplasm enzyme ACAT1 4.10E-02 3.009 acetyl-CoA acetyltransferase 1 Cytoplasm enzyme ACBD4 2.66E-03 1.722 acyl-CoA binding domain unknown other containing 4 ACSL5 1.86E-02 −2.876 acyl-CoA synthetase long-chain Cytoplasm enzyme family member 5 ADAM23 3.33E-02 −3.008 ADAM metallopeptidase domain Plasma peptidase 23 Membrane ADAM29 5.58E-03 3.463 ADAM metallopeptidase domain Plasma peptidase 29 Membrane ADAMTS17 2.67E-04 3.051 ADAM metallopeptidase with Extracellular other thrombospondin type 1 motif, 17 Space ADCYAP1R1 1.20E-02 1.848 adenylate cyclase activating Plasma G-protein polypeptide 1 (pituitary) receptor Membrane coupled type I receptor ADH6 (includes 4.02E-02 −1.845 alcohol dehydrogenase 6 (class Cytoplasm enzyme EG:130) V) AHSA2 1.54E-04 −1.6 AHA1, activator of heat shock unknown other 90kDa protein ATPase homolog 2 (yeast) AK5 3.32E-02 1.658 adenylate kinase 5 Cytoplasm kinase AK7
    [Show full text]
  • Potential for Natural Killer Cell-Mediated Antibody-Dependent Cellular Cytotoxicity for Control of Human Cytomegalovirus
    Antibodies 2013, 2, 617-635; doi:10.3390/antib2040617 OPEN ACCESS antibodies ISSN 2073-4468 www.mdpi.com/journal/antibodies Review Potential for Natural Killer Cell-Mediated Antibody-Dependent Cellular Cytotoxicity for Control of Human Cytomegalovirus Rebecca J. Aicheler *, Eddie C. Y. Wang, Peter Tomasec, Gavin W. G. Wilkinson and Richard J. Stanton Cardiff Institute of Infection and Immunity, Cardiff University, Cardiff, CF14 4XN, UK; E-Mails: [email protected] (E.C.Y.W.); [email protected] (P.T.); [email protected] (G.W.G.W.); [email protected] (R.J.S.) * Author to whom correspondence should be addressed; E-Mail: [email protected]; Tel.: +44-0-292-068-7319. Received: 31 October 2013; in revised form: 15 November 2013 / Accepted: 27 November 2013 / Published: 10 December 2013 Abstract: Human cytomegalovirus (HCMV) is an important pathogen that infects the majority of the population worldwide, yet, currently, there is no licensed vaccine. Despite HCMV encoding at least seven Natural Killer (NK) cell evasion genes, NK cells remain critical for the control of infection in vivo. Classically Antibody-Dependent Cellular Cytotoxicity (ADCC) is mediated by CD16, which is found on the surface of the NK cell in a complex with FcεRI-γ chains and/or CD3ζ chains. Ninety percent of NK cells express the Fc receptor CD16; thus, they have the potential to initiate ADCC. HCMV has a profound effect on the NK cell repertoire, such that up to 10-fold expansions of NKG2C+ cells can be seen in HCMV seropositive individuals. These NKG2C+ cells are reported to be FcεRI-γ deficient and possess variable levels of CD16+, yet have striking ADCC functions.
    [Show full text]
  • Expansions of Adaptive-Like NK Cells with a Tissue-Resident Phenotype in Human Lung and Blood
    Expansions of adaptive-like NK cells with a tissue-resident phenotype in human lung and blood Demi Brownliea,1, Marlena Scharenberga,1, Jeff E. Moldb, Joanna Hårdb, Eliisa Kekäläinenc,d,e, Marcus Buggerta, Son Nguyenf,g, Jennifer N. Wilsona, Mamdoh Al-Amerih, Hans-Gustaf Ljunggrena, Nicole Marquardta,2,3, and Jakob Michaëlssona,2 aCenter for Infectious Medicine, Department of Medicine Huddinge, Karolinska Institutet, 14152 Stockholm, Sweden; bDepartment of Cell and Molecular Biology, Karolinska Institutet, 171 77 Stockholm, Sweden; cTranslational Immunology Research Program, University of Helsinki, 00014 Helsinki, Finland; dDepartment of Bacteriology and Immunology, University of Helsinki, 00014 Helsinki, Finland; eHelsinki University Central Hospital Laboratory, Division of Clinical Microbiology, Helsinki University Hospital, 00290 Helsinki, Finland; fDepartment of Microbiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104; gInstitute for Immunology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104; and hThoracic Surgery, Department of Molecular Medicine and Surgery, Karolinska University Hospital, Karolinska Institutet, 171 76 Stockholm, Sweden Edited by Marco Colonna, Washington University in St. Louis School of Medicine, St. Louis, MO, and approved January 27, 2021 (received for review August 18, 2020) Human adaptive-like “memory” CD56dimCD16+ natural killer (NK) We and others recently identified a subset of tissue-resident − cells in peripheral blood from cytomegalovirus-seropositive indi- CD49a+CD56brightCD16 NK cells in the human lung (14, 15). viduals have been extensively investigated in recent years and are The human lung is a frequent site of infection with viruses such currently explored as a treatment strategy for hematological can- as influenza virus and HCMV, as well as a reservoir for latent cers.
    [Show full text]
  • Systems Physiology and Nutrition In
    SYSTEMS PHYSIOLOGY AND NUTRITION IN DAIRY CATTLE: APPLICATIONS OF OMICS AND BIOINFORMATICS TO BETTER UNDERSTAND THE HEPATIC METABOLOMICS AND TRANSCRIPTOMICS ADAPTATIONS IN TRANSITION DAIRY COWS BY KHURAM SHAHZAD DISSERTATION Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Informatics in the Graduate College of the University of Illinois at Urbana-Champaign, 2017 Urbana, Illinois Doctoral Committee: Associate Professor, Juan J. Loor, Chair Professor Gustavo Caetano-Anolles Associate Professor, Juan Steibel, Michigan State University Assistant Professor Phil Cardoso ABSTRACT Application of systems concepts to better understand physiological and metabolic changes in dairy cows during the transition into lactation could enhance our understanding about the role of nutrients in helping to meet the animal’s requirements for optimal production and health. Four different analyses focused on the liver were conducted to analyze metabolic disorder or thermal stress. The first three analyses dealt with supplementation of methionine to prevent clinical ketosis development in high-genetic merit dairy cows. Four groups of cows were formed retrospectively based on clinical health evaluated at 1 week postpartum: cows that remained healthy (OVE), cows that developed ketosis (K), and healthy cows supplemented with one of two commercial methionine products [Smartamine M (SM), and MetaSmart (MS)]. The liver tissue samples (n = 6/group) were harvested at -10 d before calving, and were used for metabolomics (GC-MS, LC-MS; Metabolon Inc.) and transcriptomics (44K-whole-transcriptome microarray; Agilent) analyses. Therefore, the main goals of the analyses were to 1) uncover metabolome and transcriptome patterns in the prepartum liver that were unique to those cows that became ketotic postpartum, and to 2) uncover unique patterns affected by supplemental methionine.
    [Show full text]
  • Differences in Gene Expression Profiles and Carcinogenesis Pathways Involved in Cisplatin Resistance of Four Types of Cancer
    596 ONCOLOGY REPORTS 30: 596-614, 2013 Differences in gene expression profiles and carcinogenesis pathways involved in cisplatin resistance of four types of cancer YONG YANG1,2, HUI LI1,2, SHENGCAI HOU1,2, BIN HU1,2, JIE LIU1,3 and JUN WANG1,3 1Beijing Key Laboratory of Respiratory and Pulmonary Circulation, Capital Medical University, Beijing 100069; 2Department of Thoracic Surgery, Beijing Chao-Yang Hospital, Capital Medical University, Beijing 100020; 3Department of Physiology, Capital Medical University, Beijing 100069, P.R. China Received December 23, 2012; Accepted March 4, 2013 DOI: 10.3892/or.2013.2514 Abstract. Cisplatin-based chemotherapy is the standard Introduction therapy used for the treatment of several types of cancer. However, its efficacy is largely limited by the acquired drug Cisplatin is primarily effective through DNA damage and is resistance. To date, little is known about the RNA expression widely used for the treatment of several types of cancer, such changes in cisplatin-resistant cancers. Identification of the as testicular, lung and ovarian cancer. However, the ability RNAs related to cisplatin resistance may provide specific of cancer cells to become resistant to cisplatin remains a insight into cancer therapy. In the present study, expression significant impediment to successful chemotherapy. Although profiling of 7 cancer cell lines was performed using oligo- previous studies have identified numerous mechanisms in nucleotide microarray analysis data obtained from the GEO cisplatin resistance, it remains a major problem that severely database. Bioinformatic analyses such as the Gene Ontology limits the usefulness of this chemotherapeutic agent. Therefore, (GO) and KEGG pathway were used to identify genes and it is crucial to examine more elaborate mechanisms of cisplatin pathways specifically associated with cisplatin resistance.
    [Show full text]
  • Effect of NKG2C Absence on Natural Killer Cell Phenotype and Function in Human
    Effect of NKG2C Absence on Natural Killer Cell Phenotype and Function in Human Immunodeficiency Virus/Cytomegalovirus Co-infection ©Emilie M. Comeau A thesis submitted to the School of Graduate Studies in partial fulfillment of the requirements for the degree of Master of Science in Medicine Division of BioMedical Science Immunology and Infectious Diseases Faculty of Medicine, Memorial University of Newfoundland St. John’s, Newfoundland May 2018 Abstract Natural killer (NK) cells expressing NKG2C and CD57 expand following human cytomegalovirus (CMV) infection. This NK cell subset downregulates FcεR1γ and acquires enhanced capacity to mediate antibody-dependent cellular cytotoxicity (ADCC). Expansion of these differentiated NK cells is exaggerated in human immunodeficiency virus (HIV) infection. Individuals lacking the gene encoding NKG2C have diminished resistance to HIV, but it remains unclear whether differentiation into NK cells with superior ADCC is impaired in NKG2Cnull individuals. Therefore, our objective was to investigate if CMV-driven NK cell differentiation into enhanced killers is impaired in NKG2Cnull HIV-infected individuals. Phenotypic (CD57+, FcεR1γ-) and functional (IFN- γ, TNF-α induction and cytotoxicity) NK cell responses were compared between NKG2Cnull and matched NKG2C-expressing individuals by flow cytometry following stimulation through natural cytotoxicity receptors (using K562 cells) or CD16 (using monoclonal antibody, 3G8). Cytotoxicity was measured in 51Chromium release assays against anti-CD16-coated P815 cells (redirected lysis) and anti-human leukocyte antigen (HLA) class I antibody-coated C1R cells (classical ADCC). Antibodies were titrated to determine concentrations producing half maximal responses (EC50) to compare sensitivity. Our data indicate highly similar CMV-driven NK cell differentiation in terms of both general phenotype and function, regardless of NKG2C genotype.
    [Show full text]